Comment on "An Efficient Privacy-Preserving Ranked Multi-Keyword Retrieval for Multiple Data Owners in Outsourced Cloud"

TL;DR

This paper critiques a recent privacy-preserving multi-keyword retrieval scheme, demonstrating its vulnerabilities and proposing corrections to enhance its resistance against various privacy attacks.

Contribution

It identifies flaws in Li et al.'s scheme and provides corrected equations to improve privacy protection in outsourced cloud search.

Findings

Li et al.'s scheme is vulnerable to keyword guessing attack.

The original scheme fails to protect index and trapdoor privacy.

Corrected equations enhance the scheme's privacy robustness.

Abstract

Protecting the privacy of keywords in the field of search over outsourced cloud data is a challenging task. In IEEE Transactions on Services Computing (Vol. 17 No. 2, March/April 2024), Li et al. proposed PRMKR: efficient privacy-preserving ranked multi-keyword retrieval scheme, which was claimed to resist keyword guessing attack. However, we show that the scheme fails to resist keyword guessing attack, index privacy, and trapdoor privacy. Further, we propose a solution to address the above said issues by correcting the errors in the important equations of the scheme.